Traditional robots are generally fast machinery. "The motors are fast, and they're powerful," says Sabrina Neuman.
However, in challenging situations--often involving human interaction--robots can be stubborn. "The hang-up is what's going on in the robot's head," she adds.
Perceiving stimuli and calculating a response takes a "boatload of computation," which limits reaction time, says Neuman, who recently graduated with a PhD from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).
How can we prevent the mismatch between a robot's mind and body? The answer to this is a method is known as robomorphic computing which is based on a customizable computer chip that minimizes the robot's response time.
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The development has abundant applications including assisting healthcare workers. "It would be fantastic if we could have robots that could help reduce risk for patients and hospital workers," says Neuman.
"Based on what they've seen, they have to construct a map of the world around them and then localize themselves within that map," says Neuman. The third step is motion planning and control -- in other words, plotting a course of action.
"For robots to be deployed into the field and safely operate in dynamic environments around humans, they need to be able to think and react very quickly," says Plancher. "Current algorithms cannot be run on current CPU hardware fast enough."
Neuman adds that researchers have been investigating better algorithms, but she thinks software improvements alone aren't the answer. "What's relatively new is the idea that you might also explore better hardware." That means moving beyond a standard-issue CPU processing chip that comprises a robot's brain -- with the help of hardware acceleration.
"A GPU is not the best at everything, but it's the best at what it's built for," says Neuman. "You get higher performance for a particular application."therefore tailored to maximize efficiency for the robot's computing needs. And that customization paid off in testing.
"I was thrilled with those results," says Neuman. "Even though we were hamstrung by the lower clock speed, we made up for it by just being more efficient."
"Ideally we can eventually fabricate a custom motion-planning chip for every robot, allowing them to quickly compute safe and efficient motions," he says. "I wouldn't be surprised if 20 years from now every robot had a handful of custom computer chips powering it, and this could be one of them."
Source: Science Daily